Directional Accuracy of Urban Consumers’ Inflation Forecasts in China

Ahn, Young Bin

doi:10.1080/1540496x.2017.1297933

Cited by 3 publications

(1 citation statement)

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“…In addition to the conventional error measures for evaluating the magnitude of forecast errors, this study also considers directional accuracy tests in investigating the track records of individual industry and academic experts' adjusted forecast accuracy (Ahn, 2018;Greer, 2003). The direction of change in the forecast (F) can be defined as DF tþ1 ¼ F tþ1 À F t , where F tþ1 denotes the onequarter-ahead forecasts of visitor arrivals at time t. We define an increase in the arrivals forecasts as DF t ¼ 1 when DF t > 0, and no change or a decrease as DF t ¼ 0 when DF t 0.…”

Section: Forecast Performance Evaluationmentioning

confidence: 99%

Judgmental adjustments in tourism forecasting practice: How good are they?

Lin

2018

Tourism Economics

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This study aims to evaluate the accuracy of different judgmental forecasting tasks, compare the judgmental forecasting behaviour of tourism researchers and practitioners and explore the validity of experts’ judgmental behaviour by using the Hong Kong visitor arrivals forecasts over the period 2011Q2−2015Q4. Delphi-based judgmental forecasting procedure was employed through the Hong Kong Tourism Demand Forecasting System, an online forecasting support system, to collect and combine experts’ adjusted forecasts. This study evaluates forecasting performance and explores the characteristics of judgmental adjustment behaviour through the use of a group of error measures and statistical tests. The findings suggest a positive correlation between forecast accuracy and the level of data variability, and that experts’ adjustments are more beneficial in terms of achieving higher accuracy for series with higher variability. Industry practitioners’ forecasts outperformed academic researchers, particularly in making short-term forecasts. However, no significant difference was found between the two panels in making directionally correct forecasts. Experts’ judgmental intervention was found most useful for those series most in need of adjustment. The size of adjustment was found to have a strong and significantly positive association with the direction of forecast adjustment, but no statistically significant evidence was found regarding the relationship between accuracy improvement and adjustment size.

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Section: Forecast Performance Evaluationmentioning

confidence: 99%